Description Usage Arguments Value See Also Examples
Implements the EM algorithm for a parameterized Gaussian mixture model, starting with the expectation step.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  emE(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emV(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emX(data, prior = NULL, warn = NULL, ...)
emEII(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVII(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEEI(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVEI(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEVI(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVVI(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEEE(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEEV(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVEV(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVVV(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEVE(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emEVV(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVEE(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emVVE(data, parameters, prior = NULL, control = emControl(), warn = NULL, ...)
emXII(data, prior = NULL, warn = NULL, ...)
emXXI(data, prior = NULL, warn = NULL, ...)
emXXX(data, prior = NULL, warn = NULL, ...)

data 
A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables. 
parameters 
The parameters of the model:

prior 
The default assumes no prior, but this argument allows specification of a
conjugate prior on the means and variances through the function

control 
A list of control parameters for EM. The defaults are set by the call

warn 
A logical value indicating whether or not a warning should be issued
whenever a singularity is encountered.
The default is given in 
... 
Catches unused arguments in indirect or list calls via 
A list including the following components:
modelName 
A character string identifying the model (same as the input argument). 
z 
A matrix whose 
parameters 

loglik 
The log likelihood for the data in the mixture model. 
Attributes: 

me
,
mstep
,
mclustVariance
,
mclust.options
.
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